Research On Health Monitoring Of Aero-engine Rotational Components Based On Nonlinear Estimation

The aero-engine is known as the heart of aerocraft, so the health monitoring of aero-engine is propitious to ensure flight safety. With the development of modern technology, the function of aero-engine is improved and the requirement of structure and working environment is more strict. Thus the components of aero-engine are often in trouble, affecting the whole engine. So the health monitoring of aero-engine become more and more important.In this paper, the health monitoring of aero engine rotational components based on nonlinear estimate is studied. Firstly, the component level mathematical model of aeroengine based on self-adapt specific heat is built up. Then, analyzing the balance working condition, while the balance equations of turbofan are established. Using the traditional Newton-Raphson method to solve the equations, many shortages and problems can be find.Because of the shortages and problems of traditional method, modern optimize algorithm is inducted. Firstly, Particle Swarm Optimization(PSO) algorithm is studied and the appropriate algorithm parameters are selected and designed for solving the engine model. Improving PSO algorithm, SWPSO and WCPSO can be inducted. According to the simulation, both of them with appropriate parameters get satisfied solutions, and using the two methods to solve the aeroengine model is feasible.The testing data are preprocessed using wavelet method and robust Kalman filter.On the base of analyzing reasons of components degradation, the nonlinear degradation model is established by coupling the basic balance equations with the measurement balance equations, and the estimation of component deviation parameters is changed to the problem of solving nonlinear equations.Using SWPSO and WCPSO algorithms to solve the degraded nonlinear model. The magnitude of objective function value to get the satisfied estimation results is given.The correctness of SWPSO and WCPSO algorithms is also validated while sitting fault deviation parameters. The studies are useful for engineering value, which is important to aero-engine health monitoring and faults diagnosis.